A Comprehensive Survey on Technologies in Video-based Event Detection and Recognition Using Machine Learning and Deep Learning Techniques
H Jyothi, M Komala, S Mallikarjunaswamy · 2024
Video-based event recognition systems are integral to numerous applications ranging from security surveillance to automated content analysis and interaction in smart environments. This survey provides a comprehensive review of the current methodologies and technologies employed in video-based event recognition. The research begin by exploring the foundational concepts of video processing and event detection, highlighting the evolution of techniques from rule-based systems to advanced deep learning models. The core of the survey examines various approaches, including object recognition, motion analysis, and contextual understanding, which enable the identification and classification of events in video data. This research discusses the integration of multimodal data sources to enhance recognition accuracy and robustness. Additionally, the survey addresses the challenges faced in real-world deployments such as scalability, real-time processing demands, and privacy concerns. Future trends are contemplated, focusing on the potential impacts of emerging technologies like augmented reality and edge computing on the development of more sophisticated and efficient event recognition systems. This survey aims to provide a clear and structured overview of the field, encouraging further research and innovation in developing smarter, more responsive video-based event recognition technologies.